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Author Zhongyang Xiong ♦ Yufang Zhang ♦ Ling Ou ♦ Li Li
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2005
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Neural networks ♦ Neurons ♦ Convergence ♦ Backpropagation algorithms ♦ Partitioning algorithms ♦ Computer science ♦ Feeds ♦ Robust stability ♦ Communications technology ♦ Business communication ♦ Two-phases ♦ Neural Network ♦ Parallel ♦ RPROP Algorithm
Abstract BP algorithm is widely used in the field of business intelligence. Aimed at improving its relatively slow convergence speed and its tendency to be trapped in local minima easily, an improved two-phases parallel algorithm is presented in this paper. The first parallel operation is to cast about for minima area so as to avoid getting into local optimal solution to some extent and accelerate convergence, thereby reducing the number of epochs. The second parallel operation is to shorten learning time. The experiments demonstrate that the improved two-phases parallel BP algorithm has the better performance of speedup.
Description Author affiliation: Dept. of Comput. Sci., Chongqing Univ., Chongqing (Zhongyang Xiong; Yufang Zhang; Ling Ou)
ISBN 0780393112
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-11-21
Publisher Place Australia
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 4.96 MB
Page Count 6
Starting Page 1
Ending Page 6


Source: IEEE Xplore Digital Library